| 转炉炼钢智能动态终点控制 |
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| 引用本文： | 谢书明,孙廷玉,柴天佑,陶 钧.转炉炼钢智能动态终点控制[J].控制理论与应用,2001,18(3):346-352. |
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| 作者姓名： | 谢书明 孙廷玉 柴天佑 陶 钧 |
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| 作者单位： | 1. 沈阳工业大学电气工程学院
2. 东北大学自动化研究中心 |
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| 基金项目： | supportedbyChineseNationalNaturalScienceKeyFund ( 696740 18)andChineseNational“Nine Five”Project( 97-5 62 -0 3 -0 2 ) |
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| 摘 要： | 针对转炉炼钢过程复杂，影响终点因素多，而且难以进行连续准确针测量，提出了基于副枪检测信息的智能动态终点控制方法。采用灰色模型并通过神经网络进行补偿对转炉炼钢终点温度和碳含量进行预报，在此基础上，以RBF神经网络作为预设定模型，通过模糊调整确定补吹阶段需要的氧气量和加入的冷却剂量，并对一座180吨转炉进行仿真计算，结果表明了该方法的有效性。
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| 关 键 词： | 转炉炼钢 智能控制 终点控制 神经网络 |
| 文章编号： | 1000-8152(2001)03-0346-07 |
| 收稿时间： | 2000/1/24 0:00:00 |
| 修稿时间： | 2000年1月24日 |
BOF Intelligent Dynamic Endpoint Control |
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| XIE Shu-ming,SUN Ting-yu,CHAI Tian-you and TAO Jun.BOF Intelligent Dynamic Endpoint Control[J].Control Theory & Applications,2001,18(3):346-352. |
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| Authors: | XIE Shu-ming SUN Ting-yu CHAI Tian-you and TAO Jun |
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| Affiliation: | Electric Engineering Institute,Shenyang University of Technology, Shenyang,110023,P.R.China;Electric Engineering Institute,Shenyang University of Technology, Shenyang,110023,P.R.China;Research Center of Automation, Northeastern University, Shenyang,110006,P.R.China;Research Center of Automation, Northeastern University, Shenyang,110006,P.R.China |
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| Abstract: | Being aimed at BOF (basic oxygen furnace) process which is complicated,has many factors influencing the endpoint, and is difficult to be measured continuously and accurately,the intelligent dynamic endpoint control based on the sublance information is proposed. The BOF endpoint temperature and carbon content are predicted by use of gray model and neural network compensation. On the basis of this,the RBF neural network is regarded as presetting model,and the oxygen and coolant during the reblowing period are adjusted through fuzzy adjustment.A 180t converter is simulated.The results show that the method is effective. |
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| Keywords: | BOF steelmaking intelligent control endpoint control |
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